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REU Site: Fundamental Research Topics Related to Unmanned Systems

REU Site: Fundamental Research Topics Related to Unmanned Systems
REU 网站:与无人系统相关的基础研究主题
批准号:
1359311
负责人:
Farbod Fahimi
金额:
$29.78万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-03-15 至 2017-02-28

项目摘要

项目成果

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中文摘要
翻译
技术概述:阿拉巴马大学亨茨维尔分校(UAH)本科生研究经验项目专注于五个相关科学和工程领域的基础研究缺失环节:动力学与控制、视频处理和数据挖掘与压缩、人机界面、传感器物理、材料科学。例如,这些相关领域的更广泛的社会/经济影响之一是,它们有助于影响人类生活质量的无人系统民用应用的扩散。首先,制定了基于交互的学习控制器,它只能通过与系统交互来学习如何控制系统,类似于人类学习如何用最少的指令控制机器的方式。其次,研究基于视觉的物体三维重建与分类。目标是制定一种仅使用2D视频生成任意对象的3D模型的方法,并使用2D视频对对象进行分类。此外,学生将学习分类fi蛋白质晶体生长相阳离子分类fi基于晶体存在的图像阳离子。第三,研究异构传感器数据集成的新方法。目标是能够融合从不同类型的传感器收集的数据来重建3D环境。第四,研究重点是寻找视频数据实时压缩的最佳方法。目标是制定一种优化计算能力需求、能源使用、重量和数据带宽的方法。第五,产生人机界面的新思路。目标是填补人机交互界面无法直观地解释用户意图的空白。第六,将利用物理学的基础知识来发明新的传感器,以精确实时地测量高频应变。第七,测定IPPase在不同温度、pH和离子浓度下的比催化活性。非技术总结:本科学生将接触到与他们选择的研究项目相关的最新知识和背景。他们将接受必要的研究技术、文献调查方法、产生假设、制定验证假设的测试、收集数据以及在专业和科学会议上通过书面材料和口头报告与同事沟通的培训。学生将在导师的帮助下解决研究问题,并将自己转变为相对独立的青年研究人员。研究经验和独立性为学生带来了热情和信心,并大大增加了他们在stem相关领域攻读研究生和职业的可能性。该项目鼓励美国未来科学人才的多样性。确定了阿拉巴马州和田纳西州中南部(EPSCoR州)的三所两年制学院和七所本科院校。这10所大学的学生总数中女性占51%,少数族裔占82%。通过将大部分招聘工作集中在这些机构,该计划的目标是至少从两年制大学招聘50%的学生,至少70%的女性和少数民族参与其中。学生将准备在相关会议上发表的论文,并在相关会议论文集和科学/工程期刊上发表。“该奖项是由刺激竞争性研究实验计划(EHR/EPSCoR)共同资助的。”
英文摘要
TECHNICAL SUMMARY:The University of Alabama in Huntsville (UAH) Research Experience for Undergraduates program focuses on the missing links of fundamental research in five related fields of science and engineering: Dynamics & Controls, Video Processing and Data Mining and Compression, Human-Machine Interface, Physics of Sensors, Material Science. As an example, one of the broader societal/economic impacts of these related fields is that they help the proliferation of Unmanned Systems civilian applications that affect humans quality of life. First, interaction-based learning controllers are formulated, which are able to learn how to control a system only by interacting with it, similar to the way humans learn how to control machines with minimum instructions. Second, vision-based object 3D reconstruction and classification will be researched. The goal is to formulate a method that only uses 2D videos to generate a 3D model of an arbitrary object, and classify objects using 2D video. In addition, the students will learn about data mining techniques for classification of phases of protein crystal growth classification of images based on presence of crystals. Third, new ways of integration of data from heterogeneous sensors will be researched. The goal is to be able to fuse data gathered from different sensor types to reconstruct a 3D environment. Fourth, research will be focused on finding optimum ways of real-time compression of video data. The goal is formulating a method that optimizes the need for computational power, use of energy, weight, and data bandwidth. Fifth, new ideas for human-machine interface will be generated. The objective is to fill the gap in the inability of human-agent interfaces to intuitively interpret the users intent. Sixth, fundamentals of physics will be employed to invent new sensors for accurate real-time measurement of high-frequency strain. Seventh, the specific catalytic activity of the IPPase under different temperatures, pH and ionic concentration will be determined.NON-TECHNICAL SUMMARY:The undergraduate students will be exposed to the state-of-the-art knowledge and background related to the research project of their choice. They will be trained in the required research techniques, methods of literature survey, generating hypotheses, formulating tests to validate hypotheses, collecting data, and communicating with colleagues via written materials and oral presentations at professional and scientific meetings. Students will solve research problems with the help of mentors, and will transform themselves into relatively independent young researchers. The research experience and independence generates enthusiasm and confidence for the students, and highly increases the their likelihood of pursuing graduate studies and careers in STEM-related fields. The program encourages diversity among US future scientific talent. Three two-year colleges and seven undergraduate institutions in Alabama and Central Southern Tennessee (EPSCoR states) are identified. The total student population of these ten institutions consists of 51% women and 82% minorities. By focusing most of the recruitment efforts on these institutions, the program aims for recruiting at least 50% of the students from two-year colleges and at least 70% participation by women and minorities. Students will prepare papers for presentation at relevant conferences and for publication in related conference proceedings and science/engineering journals."This award is co-funded by the Experimental Program to Stimulate Competitive Research (EHR/EPSCoR)."
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  • 批准号:
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